codebase
無料Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Codex.
日本語の概要は準備中です。原文の説明を表示しています。
Search Cognee memory. Session memory is automatically searched on every prompt via hooks. Use this skill explicitly for permanent knowledge graph search, filtered category search, or when you need more results than the automatic lookup provides.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Search both session memory and the permanent knowledge graph, optionally filtered by data category.
Session memory is searched automatically on every user prompt via the UserPromptSubmit hook. You do not need to run this skill to access current-session context.
Knowledge is organized into three categories via node_set:
| Category | Node set | Contains |
|---|---|---|
| user | user_context | User preferences, corrections, personal facts |
| project | project_docs | Repository docs, code context, architecture decisions |
| agent | agent_actions | Tool call logs, reasoning traces, generated artifacts |
POST /api/v1/recall) via the wrapper below — the source of truth in both
local and cloud mode.cognee-cli is a last resort, not an alternative. It is reachable only on a
machine holding a cognee source checkout, and in cloud mode the plugin's
venv is never built at all. Use it only when the server is genuinely
unreachable and that checkout exists. Unsure which mode you are in?
"${CLAUDE_PLUGIN_ROOT}/scripts/cognee-doctor.sh" --json reports mode,
server_url and reachable without importing cognee.Use the wrapper below: it queries the server, scoped to the plugin's dataset ($COGNEE_PLUGIN_DATASET, default agent_sessions — the same dataset all plugin writes target, so unrelated datasets don't bleed in), and resolves the endpoint, session and API key the way the hooks do.
One broad search is usually enough — the UserPromptSubmit hook already injects the graph's memory (and code-graph facts) every turn, so avoid running many targeted searches (each is an extra permission prompt for the user).
# permanent knowledge graph (the default; --graph is the same)
"${CLAUDE_PLUGIN_ROOT}/scripts/cognee-search.sh" "$ARGUMENTS" 10
# deterministic code graph (indexed repos only — see the cognee-code skill)
"${CLAUDE_PLUGIN_ROOT}/scripts/cognee-search.sh" "MyClass" 10 --code
Structural code questions belong to --code, not here. "What calls X",
"what breaks if I change X", "list all endpoints" are answered exactly and
token-free by the code graph — see the cognee-code skill for the
operations and for indexing a repository. Use this skill's semantic search for
conceptual questions that name no symbol ("how does auth work here?").
Categories (user_context / project_docs / agent_actions) filter by node set. The wrapper does not expose this — pass node_name to the server directly.
Resolve credentials first. In local mode $COGNEE_API_KEY is empty (the key is minted into ~/.cognee-plugin/api_key.json and never exported to your shell), so a hand-rolled curl with -H "X-Api-Key: ${COGNEE_API_KEY:-}" 401s and looks like a server fault when nothing is wrong. Use the forget helper's resolver in the same shell invocation — exports do not persist across separate Bash calls:
eval "$("${CLAUDE_PLUGIN_ROOT}/scripts/cognee-forget.sh" env)" && \
curl -s -X POST "${COGNEE_BASE_URL}/api/v1/recall" \
-H "Content-Type: application/json" \
-H "X-Api-Key: ${COGNEE_API_KEY}" \
-d '{"query": "...", "top_k": 5, "only_context": true, "scope": ["graph"], "node_name": ["project_docs"], "datasets": ["'"${COGNEE_PLUGIN_DATASET:-agent_sessions}"'"]}'
The server is authoritative. If a search returns empty but you expect content, confirm directly — do not conclude "not found" from empty CLI output. Resolve credentials in the same invocation, as above:
eval "$("${CLAUDE_PLUGIN_ROOT}/scripts/cognee-forget.sh" env)" && \
curl -s -X POST "${COGNEE_BASE_URL}/api/v1/recall" \
-H "Content-Type: application/json" \
-H "X-Api-Key: ${COGNEE_API_KEY}" \
-d '{"query": "...", "top_k": 5, "only_context": true, "scope": ["graph"], "datasets": ["'"${COGNEE_PLUGIN_DATASET:-agent_sessions}"'"]}'
(The server enforces auth in both modes, which is why the resolver is not optional. If the response is an {"error": ...} object rather than a list, the server was reachable but rejected/failed the request — that's an error, not "no results". A 401 after the resolver means the key really is wrong for that server; a 401 without it means nothing.)
cognee-cli is a thin client over the same server and can print empty stdout even when content exists. It also requires a cognee source checkout, so on a normal install it is simply unavailable — an absent CLI is not a Cognee fault to report. Use it only when the server is down and a checkout exists, and treat empty output as inconclusive, never as "no results":
cognee-cli recall "$ARGUMENTS" -k 5 -f json
If the CLI is missing, say the server is unreachable and show the user
"${CLAUDE_PLUGIN_ROOT}/scripts/cognee-doctor.sh" output instead.
Search is scoped to this session's active dataset. When the server answers
with an authoritative empty list (or the UserPromptSubmit header injected an
"Other Cognee datasets you can search" block), the information may simply live
in another dataset the user can read. Do not switch datasets for that — a
switch retires the session. Offer a one-off search instead:
List the candidates (every dataset this identity can read, the active one excluded; read-only datasets are searchable and included):
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/list-datasets.py" --others
The JSON has current ({name, id, ids}) and datasets
([{name, id, owner_id, current}]). The hook's hint block already names all
of them with their ids, so when it is present you can skip this call.
Ask the user which dataset to search with AskUserQuestion (single select, dataset names as options; more than four → first three plus a "More…" option and page on the next question). Include a "None, stop here" reading in the question text. Only ask when the user is actually trying to recall something — an ordinary prompt with no memory match needs no picker.
Run the graph-only search on the chosen dataset by UUID (a name only resolves among datasets this identity owns), then answer from it and say which dataset the results came from:
"${CLAUDE_PLUGIN_ROOT}/scripts/cognee-search.sh" "$ARGUMENTS" 10 --graph --dataset-id <id>
The wrapper drops the session id for any dataset other than the active one
(the session is bound to the active dataset). The active dataset, the Cognee session and where
writes go are untouched. If the user then wants that dataset for the rest
of the session, point them to /cognee-memory:cognee-switch-datasets.
Results carry a source field:
"graph" — from the permanent knowledge graph. On cognee 1.6.0 and later the
item's text is the full prompt cognee would have answered from: this
session's history, the question with the retrieved context, and the guidance
block."code" — deterministic facts from an indexed repository's code graphThe session cache is never a search source; it reaches the graph through the sync.
| Signal | Action |
|---|---|
| Need current session context | Already automatic, no action needed |
| User explicitly says "search cognee" | cognee-search.sh "<query>" (server-first) |
| "what does the codebase do" / "what did we do last time" | cognee-search.sh "<query>" 10 --graph |
| Need a specific category | use the node_name curl form above (["user_context"|"project_docs"|"agent_actions"]) |
| Auto context insufficient | cognee-search.sh "<query>" 10 (memory is graph + code only; the session cache is written, never searched) |
| Server says empty and the user is recalling something | Offer the other readable datasets (list-datasets.py --others + AskUserQuestion), then cognee-search.sh "<query>" 10 --graph --dataset-id <id> |
| Result empty but you expect content | Ground-truth via the credential-resolving curl above before concluding "not found" |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Codex.
日本語の概要は準備中です。原文の説明を表示しています。
Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Antigravity.
日本語の概要は準備中です。原文の説明を表示しています。
Index a code repository into Cognee's code graph and query it deterministically (callers, impact analysis, paths, endpoints). Use for structural code questions, "index this repo", and checking what a re-index changed.
日本語の概要は準備中です。原文の説明を表示しています。
A multi-day digest of the user's own coding-agent sessions — sessions per day and project, most-edited files, and every lesson Cognee distilled into the knowledge graph in that window. Use only when the user explicitly asks for a weekly digest, a retro, a recap or report of their recent sessions, or invokes /cognee-digest. Not for questions about code or the current task.
日本語の概要は準備中です。原文の説明を表示しています。
A multi-day digest of the user's own coding-agent sessions — sessions per day and project, most-edited files, and every lesson Cognee distilled into the knowledge graph in that window. Use only when the user explicitly asks for a weekly digest, a retro, a recap or report of their recent sessions, or asks for the `cognee-digest` skill by name. Not for questions about code or the current task.
日本語の概要は準備中です。原文の説明を表示しています。
Use when an agent must stand up the OpenClaw↔Cognee integration with FalkorDB as the vector + graph store. This skill is SELF-CONTAINED — it tells you to generate every file (Dockerfile, sitecustomize.py, docker-compose.yaml) from the exact contents below, build a custom Cognee image that loads the FalkorDB adapter, run Cognee + FalkorDB together, self-verify the adapter registered, and point the OpenClaw cognee plugin at it (including per-agent graphs). No other files in this directory are required.
日本語の概要は準備中です。原文の説明を表示しています。